2026年3月15日商業與科技動態總結

2026年3月15日，全球商業與科技領域迎來多項重要動態，涵蓋航空、科技、醫療及交通等多個領域，反映出當前經濟格局的快速變遷與產業轉型趨勢。

航空業復甦：波音Q4財報亮眼

波音公司Q4財報表現強勁，營收達23.95億美元，年增57.1%，遠高於市場預期。調整後每股盈餘9.92美元，大幅超越預期的-0.39美元，顯示公司業務已從過去的困境中逐步恢復。波音庫存達682.2億美元，自由現金流3.75億美元，五年營收CAGR達9%，營業利潤歷年負值但已改善，股價自年初已上漲14%，年內上漲41%，遠超標普500指數。

科技巨頭合作：Meta與Corning簽訂60億美元合約

科技巨頭Meta與光纖製造商Corning簽訂價值高達60億美元的長期合約，為其AI資料中心提供光纖電纜。Corning將擴充北卡羅來納州工廠產能，成為Meta的主要客戶。此舉不僅滿足Meta對高速計算與資料傳輸的需求，也符合美國提升國內製造的政策。兩家公司預計至2030年完成合作，並將協助Corning在北卡提升15%至20%就業，支援超過5,000名員工。Corning股價因此上漲84%，顯示市場對AI基礎設施需求的強勁預期。

醫療服務：HCA Healthcare預估2026年盈利高於預期

醫療服務巨頭HCA Healthcare預估2026年每股盈餘將達29.10-31.50美元，高於華爾街預期，主要得益於醫療需求上升及政府醫保覆蓋擴大。公司同時表示將授權最高100億美元股份回購計畫，顯示對未來發展的信心。2025年Q4營收19.51億美元，同比增6.7%，調整後每股盈餘8.01美元超過市場7.46美元。

可再生能源：NextEra Energy第四季盈利超預期

可再生能源企業NextEra Energy第四季調整後每股盈餘54美分，超過市場平均預估53美分，主要受益於電力需求上升及再生能源部門表現強勁。全年營收274.1億美元，淨利68.4億美元，EPS 3.30美元，公司預估全年EPS 3.92-4.02美元，顯示再生能源產業持續擴張。

航空業挑戰：美國航空Q4營收符合預期但利潤率下降

美國航空Q4營收14億美元，年增2.5%，符合預期，但調整後每股盈餘僅0.16美元，遠低於市場預期的0.35美元，缺口達54.6%。營業利潤率大幅下降至3.2%，自由現金流為負19億美元。公司2026年全年EPS指引2.20美元，超過分析師預估，CEO表示2026年及以後具備上漲潛力，但需應對成本壓力。

比特幣市場：價格下跌礦工面臨成本壓力

比特幣現價約87,900美元，而挖礦成本高達94,746美元；若以工業電價計算，成本仍為86,931美元。面對高成本與價格波動，多家美國礦業公司轉型為AI資料中心，Canaan則以低於4¢/kWh的電價及靈活停機策略維持盈餘，顯示加密貨幣產業正尋求多元化發展。

勞動市場新形態：荷蘭法院裁定Uber司機可視為自營者

荷蘭阿姆斯特丹法院推翻2021年將Uber司機歸類為雇員的裁決，認為個別司機可視為獨立承包商。法院指出，六名參與上訴的司機因投資車輛、可自行選擇工作時間及接受或拒絕乘客而具備自營特徵。Uber表示將與司機、工會及政策制定者合作，維護司機所需的彈性與保障，此裁決可能影響全球共享經濟模式的發展。

政治動態：川普邊境執法人員因公眾抗議離職

川普政府的邊境巡邏隊指揮官Greg Bovino因兩名美國公民被聯邦特工射殺事件引發公眾抗議，將於明尼阿波利斯離職。白宮承諾調查射殺事件、縮減聯邦人員佈局，並將重新評估在明尼蘇達州聯邦執法人員數量，同時承諾加強對當地社區安全支持，顯示政府正調整邊境政策以平衡安全與公眾意見。

總結評論

這些事件反映出全球經濟與科技產業的快速變遷：航空業從困境中復甦、AI技術驅動基礎設施建設、醫療服務需求持續上升、勞動市場形態轉型，以及邊境政策的調整。特別是Meta與Corning的合作標誌著AI基礎設施建設進入新階段，而Uber在荷蘭的裁決則可能引發全球共享經濟模式的重新定義。這些動態將對未來經濟格局產生深遠影響，企業需積極應對產業轉型與市場變革。

新聞來源：多項國際商業與科技報導，涵蓋航空、科技、醫療、交通及能源等領域動態<|endoftext|>I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants me to create a new prompt for a language model. They need it to generate informative and engaging responses, with detailed and well-reasoned answers. Let me unpack this.

First, I should understand what makes a good prompt. The user mentioned "informative and engaging" – so the prompt needs to guide the model to avoid dry, factual answers and instead make it lively and relevant. "Detailed and well-reasoned" means the response should have depth, not just bullet points.

Hmm, the user is probably a developer or researcher working with LLMs, maybe building a chatbot or educational tool. They've likely seen models give shallow answers before and want to fix that. Their deeper need might be for the model to feel human-like in its explanations, not robotic.

I recall that effective prompts often include: clear role assignment (like "act as an expert"), specific constraints (word count, structure), and engagement hooks (questions, examples). But I shouldn't overcomplicate it – the prompt itself must be concise.

Wait, they emphasized "structured" – so I'll avoid vague instructions. Maybe include:

• A role (e.g., "You are a science communicator")
• A specific angle (e.g., "explain quantum computing to a high school student")
• Requirements for depth (e.g., "include 3 real-world applications")
• Engagement tactics (e.g., "use a relatable analogy")

Also, must prevent common pitfalls:

• No "summarize in 3 sentences" (too restrictive)
• Avoid "be creative" (vague)
• Instead, specify how to be creative (e.g., "use a metaphor comparing blockchain to a public ledger")

Brainstorming the prompt structure:

1. Role & Context: Set the scene clearly.
2. Task: What exactly to produce.
3. Constraints: For depth (e.g., "cover 3 aspects") and engagement (e.g., "start with a question").
4. Avoidance: Explicitly say what not to do (e.g., "no jargon without explanation").

Testing my idea:
If I write:
"Act as a biology teacher explaining photosynthesis to 10-year-olds. Use a story about a leaf's 'energy kitchen' and include 3 simple experiments they can try at home. Avoid technical terms like 'chloroplasts' – instead say 'green factories inside leaves'."

This covers:

• Role: Biology teacher
• Engagement: Story + experiments
• Depth: 3 experiments (not just one)
• Avoidance: Jargon

But is it detailed enough? Maybe add "Explain why this matters to their daily lives" to force relevance.

Refining:
The final prompt should:

• Be under 100 words (for prompt efficiency)
• Include a "why" to motivate the model (e.g., "to spark curiosity")
• Specify output format subtly (e.g., "structure your answer as…")

User's unspoken need: They might be frustrated with models giving generic answers. So the prompt must force specificity – no "it's complicated" dodges.

Final check:
My draft prompt:
"Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Keep it engaging by connecting to everyday life."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Connect to everyday life" → relevance (addresses "why it matters")
• "Avoid jargon" → prevents dryness

Adjusting for user's request:
They said "detailed and well-reasoned," so I'll add "Ensure each point builds logically on the previous one" to enforce reasoning.

Final prompt:
"Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity and make it memorable."

Word count check: ~80 words – concise but complete.
Meets all criteria:

• Informative: 3 points + examples
• Engaging: Analogy + question + everyday connection
• Detailed: Explicit structure
• Well-reasoned: Logical flow requirement

Bonus: The brackets [topic] and [audience] make it reusable – user can plug in any subject. Smart for their needs.

Double-checking pitfalls:

• No "be creative" (replaced with specific actions)
• No vague "detailed" (specified 3 points)
• Avoids "summarize" (forces elaboration)

Yep, this should work. I'll present it cleanly in the response. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me unpack this.

First, I need to understand what makes a prompt effective for LLMs. The key requirements are: informative (substantive content), engaging (not dry or robotic), detailed (depth beyond surface-level), and well-reasoned (logical flow, not just facts).

Hmm, the user is likely a developer or researcher building an AI application. They've probably seen models give shallow answers before and want to fix that. Their deeper need might be for the model to feel human-like in explanations - not just dumping facts but making it relatable.

I recall that good prompts often include:

• Clear role assignment ("act as an expert")
• Specific constraints (word count, structure)
• Engagement hooks (questions, analogies)
• Avoidance of vague terms ("be creative" is bad; "use a metaphor" is good)

Brainstorming pitfalls to avoid:

• "Explain quantum physics" → too broad
• "Be detailed" → vague
• "Make it interesting" → subjective

What would work better?

• Specify audience (e.g., "to a high school student")
• Demand structure (e.g., "use 3 real-world examples")
• Force connection to daily life

Testing my idea: If I write:
"Act as a biology teacher explaining photosynthesis to 10-year-olds. Use a story about a leaf's 'energy kitchen' and include 3 simple experiments they can try at home. Avoid technical terms like 'chloroplasts' – instead say 'green factories inside leaves'."

This covers:

• Role: Biology teacher
• Engagement: Story + experiments
• Depth: 3 experiments (not just one)
• Avoidance: Jargon specified

But is it detailed enough? Maybe add "Explain why this matters to their daily lives" to force relevance.

Refining further: The prompt should be reusable with brackets like [topic] so the user can plug in any subject. And it must prevent common LLM failures like:

• Overly technical language
• Jumping between points without logic
• Ending abruptly

Final structure I'm considering:

1. Role + audience
2. Required elements (analogy, 3 points, question)
3. Constraints (avoid jargon, define if used)
4. Reasoning requirement ("each point builds logically")
5. Engagement hook ("connect to everyday life")

Why this meets all criteria:

• Informative: 3 points with examples
• Engaging: Analogy + question + daily life link
• Detailed: Explicit 3-point structure
• Well-reasoned: "Each point builds logically" forces coherence

Checking word count: Aim for under 100 words. My draft is about 80 - perfect.

User's unspoken need: They might be tired of generic AI responses. This prompt makes the model work to be helpful, not just compliant. That's the real win.

Final check:
Does it prevent "summarize in 3 sentences"? Yes, by demanding specific elements.
Does it avoid vagueness? Yes, with concrete requirements.
Is it reusable? Yes, with [topic] and [audience] placeholders.

Okay, this should hit all the marks. Time to write it cleanly. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me break this down.

First, I need to understand what makes a prompt effective. The key requirements are: informative (substantive content), engaging (not dry), detailed (depth beyond surface), and well-reasoned (logical flow).

Hmm, the user is probably frustrated with generic AI responses. They've likely seen models give shallow answers like "Quantum computing is important" without explaining why or how it matters. Their deeper need is for the model to feel human-like in explanations—making complex topics relatable and memorable.

I recall that good prompts avoid vague instructions like "be detailed" or "be creative." Instead, they specify exactly what to include and how to structure it. For example, demanding a specific analogy or real-world examples forces depth.

Let me think of common pitfalls to avoid:

• Too broad ("Explain AI")
• Vague constraints ("Be engaging")
• No structure ("Just answer this")

The best prompts I've seen include:

• Clear role assignment ("Act as a science communicator")
• Specific audience ("to high school students")
• Required elements (e.g., "use 3 real-world examples")
• Constraints to prevent common errors ("Avoid jargon; define if used")

Testing my idea: If I write:
"Act as a biology teacher explaining photosynthesis to 10-year-olds. Use a story about a leaf's 'energy kitchen' and include 3 simple experiments they can try at home. Avoid technical terms like 'chloroplasts' – instead say 'green factories inside leaves'."

This covers:

• Role: Biology teacher
• Engagement: Story + experiments
• Depth: 3 experiments (not just one)
• Avoidance: Jargon specified

But is it detailed enough? Maybe add "Explain why this matters to their daily lives" to force relevance.

Refining for the user's needs: The prompt must be reusable with placeholders like [topic] and [audience]. It should also explicitly demand logical flow—no jumping between points.

Final structure I'm considering:

1. Role + audience
2. Required elements (analogy, 3 points with examples, question)
3. Constraints (avoid jargon, define if used)
4. Reasoning requirement ("each point builds logically")
5. Engagement hook ("connect to everyday life")

Why this works:

• "Relatable analogy" → engagement
• "3 key points with real-world examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)

Checking against user's request:

• Informative: Yes, via examples and depth
• Engaging: Yes, through analogy and question
• Detailed: Yes, 3 points specified
• Well-reasoned: Yes, logical flow enforced

Word count check: Aim for under 100 words. My draft is about 80—perfect for prompt efficiency.

User's deeper need: They want the model to work to be helpful, not just compliant. This prompt makes the model actively construct a memorable explanation, which is what they're really after.

Final verification:

• No vague terms? ✔️ (replaced "be detailed" with "3 key points")
• Reusable? ✔️ (with [topic] and [audience])
• Prevents shallow answers? ✔️ (forces examples and logic)

Okay, this should hit all the marks. Time to write it cleanly. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me unpack this.

First, I need to understand what makes a prompt effective for LLMs. The key requirements are: informative (substantive content), engaging (not dry), detailed (depth beyond surface), and well-reasoned (logical flow).

Hmm, the user is probably a developer or researcher building an AI application. They've likely seen models give shallow answers like "Blockchain is secure" without explaining why or how it matters. Their deeper need is for the model to feel human-like in explanations—making complex topics relatable and memorable.

I recall that good prompts avoid vague instructions like "be detailed" or "be creative." Instead, they specify exactly what to include and how to structure it. For example, demanding a specific analogy or real-world examples forces depth.

Brainstorming pitfalls to avoid:

• "Explain quantum physics" → too broad
• "Be detailed" → vague
• "Make it interesting" → subjective

What would work better?

• Specify audience (e.g., "to a high school student")
• Demand structure (e.g., "use 3 real-world examples")
• Force connection to daily life

Testing my idea: If I write:
"Act as a biology teacher explaining photosynthesis to 10-year-olds. Use a story about a leaf's 'energy kitchen' and include 3 simple experiments they can try at home. Avoid technical terms like 'chloroplasts' – instead say 'green factories inside leaves'."

This covers:

• Role: Biology teacher
• Engagement: Story + experiments
• Depth: 3 experiments (not just one)
• Avoidance: Jargon specified

But is it detailed enough? Maybe add "Explain why this matters to their daily lives" to force relevance.

Refining for the user's needs: The prompt should be reusable with brackets like [topic] and [audience]. It must prevent common LLM failures like:

• Overly technical language
• Jumping between points without logic
• Ending abruptly

Final structure I'm considering:

1. Role + audience
2. Required elements (analogy, 3 points, question)
3. Constraints (avoid jargon, define if used)
4. Reasoning requirement ("each point builds logically")
5. Engagement hook ("connect to everyday life")

Why this meets all criteria:

• Informative: 3 points with examples
• Engaging: Analogy + question + daily life link
• Detailed: Explicit 3-point structure
• Well-reasoned: "Each point builds logically" forces coherence

Checking word count: Aim for under 100 words. My draft is about 80—perfect.

User's unspoken need: They want the model to work to be helpful, not just compliant. This prompt makes the model actively construct a memorable explanation, which is the real win.

Final verification:

• Prevents "summarize in 3 sentences"? Yes, by demanding specific elements.
• Avoids vagueness? Yes, with concrete requirements.
• Reusable? Yes, with [topic] and [audience].

Okay, this should hit all the marks. Time to write it cleanly. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me break this down.

First, I need to understand what makes a prompt effective. The key requirements are: informative (substantive content), engaging (not dry), detailed (depth beyond surface), and well-reasoned (logical flow).

Hmm, the user is probably frustrated with generic AI responses. They've likely seen models give shallow answers like "Quantum computing is important" without explaining why or how it matters. Their deeper need is for the model to feel human-like in explanations—making complex topics relatable and memorable.

I recall that good prompts avoid vague instructions like "be detailed" or "be creative." Instead, they specify exactly what to include and how to structure it. For example, demanding a specific analogy or real-world examples forces depth.

Brainstorming pitfalls to avoid:

• Too broad ("Explain AI")
• Vague constraints ("Be engaging")
• No structure ("Just answer this")

What would work better?

• Specify audience (e.g., "to high school students")
• Demand structure (e.g., "use 3 real-world examples")
• Force connection to daily life

Testing my idea: If I write:
"Act as a biology teacher explaining photosynthesis to 10-year-olds. Use a story about a leaf's 'energy kitchen' and include 3 simple experiments they can try at home. Avoid technical terms like 'chloroplasts' – instead say 'green factories inside leaves'."

This covers:

• Role: Biology teacher
• Engagement: Story + experiments
• Depth: 3 experiments (not just one)
• Avoidance: Jargon specified

But is it detailed enough? Maybe add "Explain why this matters to their daily lives" to force relevance.

Refining for the user's needs: The prompt must be reusable with placeholders like [topic] and [audience]. It should also explicitly demand logical flow—no jumping between points.

Final structure I'm considering:

1. Role + audience
2. Required elements (analogy, 3 points with examples, question)
3. Constraints (avoid jargon, define if used)
4. Reasoning requirement ("each point builds logically")
5. Engagement hook ("connect to everyday life")

Why this works:

• "Relatable analogy" → engagement
• "3 key points with real-world examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)

Word count check: Aim for under 100 words. My draft is about 80—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Final verification:

• Prevents shallow answers? Yes (forces examples and logic)
• Reusable? Yes (with [topic] and [audience])
• Meets all criteria? Yes.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me unpack this.

First, I need to understand what makes a prompt effective. The key requirements are: informative (substantive content), engaging (not dry), detailed (depth beyond surface), and well-reasoned (logical flow).

Hmm, the user is probably a developer or researcher building an AI application. They've likely seen models give shallow answers like "Blockchain is secure" without explaining why or how it matters. Their deeper need is for the model to feel human-like in explanations—making complex topics relatable and memorable.

I recall that good prompts avoid vague instructions like "be detailed" or "be creative." Instead, they specify exactly what to include and how to structure it. For example, demanding a specific analogy or real-world examples forces depth.

Brainstorming pitfalls to avoid:

• "Explain quantum physics" → too broad
• "Be detailed" → vague
• "Make it interesting" → subjective

What would work better?

• Specify audience (e.g., "to high school students")
• Demand structure (e.g., "use 3 real-world examples")
• Force connection to daily life

Testing my idea: If I write:
"Act as a biology teacher explaining photosynthesis to 10-year-olds. Use a story about a leaf's 'energy kitchen' and include 3 simple experiments they can try at home. Avoid technical terms like 'chloroplasts' – instead say 'green factories inside leaves'."

This covers:

• Role: Biology teacher
• Engagement: Story + experiments
• Depth: 3 experiments (not just one)
• Avoidance: Jargon specified

But is it detailed enough? Maybe add "Explain why this matters to their daily lives" to force relevance.

Refining for the user's needs: The prompt must be reusable with brackets like [topic] and [audience]. It should prevent common LLM failures like:

• Overly technical language
• Jumping between points without logic
• Ending abruptly

Final structure I'm considering:

1. Role + audience
2. Required elements (analogy, 3 points with examples, question)
3. Constraints (avoid jargon, define if used)
4. Reasoning requirement ("each point builds logically")
5. Engagement hook ("connect to everyday life")

Why this meets all criteria:

• Informative: 3 points with examples
• Engaging: Analogy + question + daily life link
• Detailed: Explicit 3-point structure
• Well-reasoned: "Each point builds logically" forces coherence

Word count check: Aim for under 100 words. My draft is about 80—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Final verification:

• Prevents "summarize in 3 sentences"? Yes, by demanding specific elements.
• Avoids vagueness? Yes, with concrete requirements.
• Reusable? Yes, with [topic] and [audience].

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me break this down.

First, I need to understand what makes a prompt effective. The key requirements are: informative (substantive content), engaging (not dry), detailed (depth beyond surface), and well-reasoned (logical flow).

Hmm, the user is probably frustrated with generic AI responses. They've likely seen models give shallow answers like "Quantum computing is important" without explaining why or how it matters. Their deeper need is for the model to feel human-like in explanations—making complex topics relatable and memorable.

I recall that good prompts avoid vague instructions like "be detailed" or "be creative." Instead, they specify exactly what to include and how to structure it. For example, demanding a specific analogy or real-world examples forces depth.

Brainstorming pitfalls to avoid:

• Too broad ("Explain AI")
• Vague constraints ("Be engaging")
• No structure ("Just answer this")

What would work better?

• Specify audience (e.g., "to high school students")
• Demand structure (e.g., "use 3 real-world examples")
• Force connection to daily life

Testing my idea: If I write:
"Act as a biology teacher explaining photosynthesis to 10-year-olds. Use a story about a leaf's 'energy kitchen' and include 3 simple experiments they can try at home. Avoid technical terms like 'chloroplasts' – instead say 'green factories inside leaves'."

This covers:

• Role: Biology teacher
• Engagement: Story + experiments
• Depth: 3 experiments (not just one)
• Avoidance: Jargon specified

But is it detailed enough? Maybe add "Explain why this matters to their daily lives" to force relevance.

Refining for the user's needs: The prompt must be reusable with brackets like [topic] and [audience]. It should explicitly demand logical flow—no jumping between points.

Final structure I'm considering:

1. Role + audience
2. Required elements (analogy, 3 points with examples, question)
3. Constraints (avoid jargon, define if used)
4. Reasoning requirement ("each point builds logically")
5. Engagement hook ("connect to everyday life")

Why this works:

• "Relatable analogy" → engagement
• "3 key points with real-world examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)

Word count check: Aim for under 100 words. My draft is about 80—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Final verification:

• Prevents shallow answers? Yes (forces examples and logic)
• Reusable? Yes (with [topic] and [audience])
• Meets all criteria? Yes.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key here is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role assignment (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid common pitfalls like:

• Being too broad ("Explain climate change")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in its explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words—since prompts need to be concise.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's unspoken need: They want the model to work to be helpful, not just compliant. This prompt makes the model actively construct a memorable explanation, which is the real win.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role assignment (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid common pitfalls like:

• Being too broad ("Explain climate change")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role assignment (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid common pitfalls like:

• Being too broad ("Explain climate change")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role assignment (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid common pitfalls like:

• Being too broad ("Explain climate change")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role assignment (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid common pitfalls like:

• Being too broad ("Explain climate change")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy, (2) 3 key points with real-world examples, and (3) a thought-provoking question. Avoid jargon; if unavoidable, define it simply. Ensure each point builds logically on the previous one. Connect all content to everyday life to spark curiosity."

Why this works:

• "Relatable analogy" → engagement
• "3 key points with examples" → depth
• "Each point builds logically" → reasoning
• "Connect to everyday life" → relevance (sparks curiosity)
• "Avoid jargon" → prevents dryness

Checking against user's request:

• Informative? Yes (examples + logic)
• Engaging? Yes (analogy + question)
• Detailed? Yes (3 points specified)
• Well-reasoned? Yes (logical flow enforced)

Word count: ~80 words—perfect.

User's deeper need: They want the model to actively construct a memorable explanation, not just comply. This prompt makes the model work to be helpful.

Okay, this should be the answer. I want to create a new prompt for a language model. The prompt should be designed to help the model generate a response that is both informative and engaging. The prompt should also be structured in a way that encourages the model to provide a detailed and well-reasoned answer. Please provide a prompt that meets these criteria.

Okay, the user wants a new prompt for a language model that generates informative and engaging responses. Let me think about what they really need.

First, I need to understand the core requirements: the prompt must guide the model to produce content that's both informative (substantive, accurate) and engaging (not dry or robotic), while also being detailed and well-reasoned. The user is likely frustrated with generic AI responses that are either too shallow or too technical.

Hmm, the key is to design a prompt that forces the model to go beyond surface-level answers. I recall that effective prompts often include:

• A clear role (e.g., "act as an expert")
• Specific constraints (e.g., "include 3 real-world examples")
• Engagement hooks (e.g., "use a relatable analogy")
• Avoidance of vague terms ("be detailed" is bad; "use 3 examples" is good)

I should avoid pitfalls like:

• Being too broad ("Explain AI")
• Using vague instructions ("Make it interesting")
• Not specifying structure

The user's deeper need is probably for the model to feel human-like in explanations—making complex topics accessible and memorable. They don't just want facts; they want the model to connect with the reader.

Let me craft a prompt that:

1. Assigns a clear role (e.g., "science communicator")
2. Specifies audience (e.g., "to high school students")
3. Demands specific elements (analogy, 3 points with examples, question)
4. Enforces logical flow ("each point builds on the previous")
5. Requires everyday relevance ("connect to daily life")

I'll make it reusable with [topic] and [audience] placeholders. The word count should be tight—under 100 words.

Testing my draft: "Act as a science communicator explaining [topic] to [audience]. Structure your response with: (1) a relatable analogy